Cancer and HIV-1 Infection: Patterns of Chronic Antigen Exposure
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
IL-7 Receptor Blockade Blunts Antigen-Specific Memory T Cell
ARTICLE DOI: 10.1038/s41467-018-06804-y OPEN IL-7 receptor blockade blunts antigen-specific memory T cell responses and chronic inflammation in primates Lyssia Belarif1,2, Caroline Mary1,2, Lola Jacquemont1, Hoa Le Mai1, Richard Danger1, Jeremy Hervouet1, David Minault1, Virginie Thepenier1,2, Veronique Nerrière-Daguin1, Elisabeth Nguyen1, Sabrina Pengam1,2, Eric Largy3,4, Arnaud Delobel3, Bernard Martinet1, Stéphanie Le Bas-Bernardet1,5, Sophie Brouard1,5, Jean-Paul Soulillou1, Nicolas Degauque 1,5, Gilles Blancho1,5, Bernard Vanhove1,2 & Nicolas Poirier1,2 1234567890():,; Targeting the expansion of pathogenic memory immune cells is a promising therapeutic strategy to prevent chronic autoimmune attacks. Here we investigate the therapeutic efficacy and mechanism of new anti-human IL-7Rα monoclonal antibodies (mAb) in non-human primates and show that, depending on the target epitope, a single injection of antagonistic anti-IL-7Rα mAbs induces a long-term control of skin inflammation despite repeated antigen challenges in presensitized monkeys. No modification in T cell numbers, phenotype, function or metabolism is observed in the peripheral blood or in response to polyclonal stimulation ex vivo. However, long-term in vivo hyporesponsiveness is associated with a significant decrease in the frequency of antigen-specific T cells producing IFN-γ upon antigen resti- mulation ex vivo. These findings indicate that chronic antigen-specific memory T cell responses can be controlled by anti-IL-7Rα mAbs, promoting and maintaining remission in T- cell mediated chronic inflammatory diseases. 1 Centre de Recherche en Transplantation et Immunologie (CRTI) UMR1064, INSERM, Université de Nantes, Nantes 44093, France. 2 OSE Immunotherapeutics, Nantes 44200, France. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
CD226 T Cells Expressing the Receptors TIGIT and Divergent Phenotypes of Human Regulatory
The Journal of Immunology Divergent Phenotypes of Human Regulatory T Cells Expressing the Receptors TIGIT and CD226 Christopher A. Fuhrman,*,1 Wen-I Yeh,*,1 Howard R. Seay,* Priya Saikumar Lakshmi,* Gaurav Chopra,† Lin Zhang,* Daniel J. Perry,* Stephanie A. McClymont,† Mahesh Yadav,† Maria-Cecilia Lopez,‡ Henry V. Baker,‡ Ying Zhang,x Yizheng Li,{ Maryann Whitley,{ David von Schack,x Mark A. Atkinson,* Jeffrey A. Bluestone,‡ and Todd M. Brusko* Regulatory T cells (Tregs) play a central role in counteracting inflammation and autoimmunity. A more complete understanding of cellular heterogeneity and the potential for lineage plasticity in human Treg subsets may identify markers of disease pathogenesis and facilitate the development of optimized cellular therapeutics. To better elucidate human Treg subsets, we conducted direct transcriptional profiling of CD4+FOXP3+Helios+ thymic-derived Tregs and CD4+FOXP3+Helios2 T cells, followed by comparison with CD4+FOXP32Helios2 T conventional cells. These analyses revealed that the coinhibitory receptor T cell Ig and ITIM domain (TIGIT) was highly expressed on thymic-derived Tregs. TIGIT and the costimulatory factor CD226 bind the common ligand CD155. Thus, we analyzed the cellular distribution and suppressive activity of isolated subsets of CD4+CD25+CD127lo/2 T cells expressing CD226 and/or TIGIT. We observed TIGIT is highly expressed and upregulated on Tregs after activation and in vitro expansion, and is associated with lineage stability and suppressive capacity. Conversely, the CD226+TIGIT2 population was associated with reduced Treg purity and suppressive capacity after expansion, along with a marked increase in IL-10 and effector cytokine production. These studies provide additional markers to delineate functionally distinct Treg subsets that may help direct cellular therapies and provide important phenotypic markers for assessing the role of Tregs in health and disease. -
Single-Cell RNA Sequencing Demonstrates the Molecular and Cellular Reprogramming of Metastatic Lung Adenocarcinoma
ARTICLE https://doi.org/10.1038/s41467-020-16164-1 OPEN Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma Nayoung Kim 1,2,3,13, Hong Kwan Kim4,13, Kyungjong Lee 5,13, Yourae Hong 1,6, Jong Ho Cho4, Jung Won Choi7, Jung-Il Lee7, Yeon-Lim Suh8,BoMiKu9, Hye Hyeon Eum 1,2,3, Soyean Choi 1, Yoon-La Choi6,10,11, Je-Gun Joung1, Woong-Yang Park 1,2,6, Hyun Ae Jung12, Jong-Mu Sun12, Se-Hoon Lee12, ✉ ✉ Jin Seok Ahn12, Keunchil Park12, Myung-Ju Ahn 12 & Hae-Ock Lee 1,2,3,6 1234567890():,; Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell tran- scriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions. 1 Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Multiomics of Azacitidine-Treated AML Cells Reveals Variable And
Multiomics of azacitidine-treated AML cells reveals variable and convergent targets that remodel the cell-surface proteome Kevin K. Leunga, Aaron Nguyenb, Tao Shic, Lin Tangc, Xiaochun Nid, Laure Escoubetc, Kyle J. MacBethb, Jorge DiMartinob, and James A. Wellsa,1 aDepartment of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143; bEpigenetics Thematic Center of Excellence, Celgene Corporation, San Francisco, CA 94158; cDepartment of Informatics and Predictive Sciences, Celgene Corporation, San Diego, CA 92121; and dDepartment of Informatics and Predictive Sciences, Celgene Corporation, Cambridge, MA 02140 Contributed by James A. Wells, November 19, 2018 (sent for review August 23, 2018; reviewed by Rebekah Gundry, Neil L. Kelleher, and Bernd Wollscheid) Myelodysplastic syndromes (MDS) and acute myeloid leukemia of DNA methyltransferases, leading to loss of methylation in (AML) are diseases of abnormal hematopoietic differentiation newly synthesized DNA (10, 11). It was recently shown that AZA with aberrant epigenetic alterations. Azacitidine (AZA) is a DNA treatment of cervical (12, 13) and colorectal (14) cancer cells methyltransferase inhibitor widely used to treat MDS and AML, can induce interferon responses through reactivation of endoge- yet the impact of AZA on the cell-surface proteome has not been nous retroviruses. This phenomenon, termed viral mimicry, is defined. To identify potential therapeutic targets for use in com- thought to induce antitumor effects by activating and engaging bination with AZA in AML patients, we investigated the effects the immune system. of AZA treatment on four AML cell lines representing different Although AZA treatment has demonstrated clinical benefit in stages of differentiation. The effect of AZA treatment on these AML patients, additional therapeutic options are needed (8, 9). -
Nectin-2 Expression on Malignant Plasma Cells Is Associated with Better Response To
Author Manuscript Published OnlineFirst on June 8, 2020; DOI: 10.1158/1078-0432.CCR-19-3673 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Nectin-2 expression on malignant plasma cells is associated with better response to TIGIT blockade in multiple myeloma Authors: Ester Lozano1,2*, Mari-Pau Mena1, Tania Díaz1, Beatriz Martin-Antonio1,3, Sheila León1, Luis-Gerardo Rodríguez-Lobato1, Aina Oliver-Caldés1, Mª Teresa Cibeira1, Joan Bladé1, Aleix Prat4, Laura Rosiñol1, and Carlos Fernández de Larrea1* Affiliations: 1Department of Hematology. Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 2Department of Cell Biology, Physiology and Immunology, Faculty of Biology, University of Barcelona, and Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Spain 3Josep Carreras Leukaemia Research Institute, Barcelona, Spain 4Department of Medical Oncology, Hospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain *Corresponding authors: Carlos Fernández de Larrea, MD PhD, Department of Hematology, Hospital Clínic de Barcelona, Villarroel Street, 170, 08036 Barcelona, Spain. Phone:+34 932275428; email [email protected] Ester Lozano PhD, Department of Cell Biology, Physiology and Immunology, Faculty of Biology, University of Barcelona Diagonal Av. 643, 3rd floor 08028 Barcelona, Spain. Phone:+34 627 37 2188; email [email protected] Running Title: TIGIT blockade associated with nectin-2 in myeloma Keywords: TIGIT, PVR, nectin-2, immune checkpoints, myeloma, MGUS Metadata: Word count: 4547 Figures: 6 Supplementary Tables: 2 Supplementary Figures: 2 CONFLICT OF INTEREST DISCLOSURE STATEMENT The authors declare no potential conflicts of interest. -
Natural Killer Cell Lymphoma Shares Strikingly Similar Molecular Features
Leukemia (2011) 25, 348–358 & 2011 Macmillan Publishers Limited All rights reserved 0887-6924/11 www.nature.com/leu ORIGINAL ARTICLE Natural killer cell lymphoma shares strikingly similar molecular features with a group of non-hepatosplenic cd T-cell lymphoma and is highly sensitive to a novel aurora kinase A inhibitor in vitro J Iqbal1, DD Weisenburger1, A Chowdhury2, MY Tsai2, G Srivastava3, TC Greiner1, C Kucuk1, K Deffenbacher1, J Vose4, L Smith5, WY Au3, S Nakamura6, M Seto6, J Delabie7, F Berger8, F Loong3, Y-H Ko9, I Sng10, X Liu11, TP Loughran11, J Armitage4 and WC Chan1, for the International Peripheral T-cell Lymphoma Project 1Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA; 2Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE, USA; 3Departments of Pathology and Medicine, University of Hong Kong, Queen Mary Hospital, Hong Kong, China; 4Division of Hematology and Oncology, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA; 5College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA; 6Departments of Pathology and Cancer Genetics, Aichi Cancer Center Research Institute, Nagoya University, Nagoya, Japan; 7Department of Pathology, University of Oslo, Norwegian Radium Hospital, Oslo, Norway; 8Department of Pathology, Centre Hospitalier Lyon-Sud, Lyon, France; 9Department of Pathology, Samsung Medical Center, Sungkyunkwan University, Seoul, Korea; 10Department of Pathology, Singapore General Hospital, Singapore and 11Penn State Hershey Cancer Institute, Pennsylvania State University College of Medicine, Hershey, PA, USA Natural killer (NK) cell lymphomas/leukemias are rare neo- Introduction plasms with an aggressive clinical behavior. -
Ncounter Fibrosis Panel
PRODUCT BULLETIN nCounter® Fibrosis Panel Gene Expression Panel Four Stages of Fibrosis • Disease Pathogenesis • Biomarkers of Progression Uncover the mechanisms of disease pathogenesis, identify biomarkers of progression, and develop signatures for therapeutic response with the nCounter Fibrosis Panel. This gene expression panel combines hundreds of genes involved in the initial tissue damage response, chronic inflammation, proliferation of pro-fibrotic cells, and tissue modification that leads to fibrotic disease of the lungs, heart, liver, kidney, and skin. INITIATION Product Highlights • Profile 770 genes across 51 annotated pathways involved in the four stages of fibrosis T is s s • Initiation s u e e r I • t D N Inflammation N S a F l m • Proliferation O l L I e a A g • Modification T C M e A M C • I Study pathogenesis and identify biomarkers for fibrotic A F I T diseases of the lungs, heart, liver, kidney, and skin I D O O N • Understand the signaling cascade from cell M stress to inflammation • Quantify the relative abundance of 14 different W g ound Healin immune cell types • Identify biomarkers of therapeutic response PR N OLIFERATIO Feature Specifications Number of Targets 770 (Human), 770 (Mouse), including internal reference genes Standard Input Material (No amplification required) 25-300 ng Sample Input - Low Input As little as 1 ng with nCounter Low Input Kit (sold separately) Cultured cells/cell lysates, sorted cells, FFPE-derived RNA, total RNA, Sample Type(s) fragmented RNA, PBMCs, and whole blood/plasma Add up to 55 unique genes with Panel-Plus and up to 10 custom Customizable protein targets Time to Results Approximately 24 hours Data Analysis nSolver™ Analysis Software (RUO) FOR RESEARCH USE ONLY. -
Interleukin-7 and Immunosenescence
Hindawi Journal of Immunology Research Volume 2017, Article ID 4807853, 17 pages https://doi.org/10.1155/2017/4807853 Review Article Interleukin-7 and Immunosenescence Vanloan Nguyen, Andrew Mendelsohn, and James W. Larrick Panorama Research Institute, 1230 Bordeaux Drive, Sunnyvale, CA 94089, USA Correspondence should be addressed to Vanloan Nguyen; [email protected] Received 6 December 2016; Revised 1 February 2017; Accepted 19 February 2017; Published 6 April 2017 Academic Editor: Alessandra Santos Copyright © 2017 Vanloan Nguyen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The age of an individual is an important, independent risk factor for many of the most common diseases afflicting modern societies. Interleukin-7 (IL-7) plays a central, critical role in the homeostasis of the immune system. Recent studies support a critical role for IL-7 in the maintenance of a vigorous healthspan. We describe the role of IL-7 and its receptor in immunosenescence, the aging of the immune system. An understanding of the role that IL-7 plays in aging may permit parsimonious preventative or therapeutic solutions for diverse conditions. Perhaps IL-7 might be used to “tune” the immune system to optimize human healthspan and longevity. 1. Introduction To understand the IL-7 network, we begin with a descrip- tion of IL-7, the IL-7 receptor, and downstream signal trans- One’s chronological age is an important, independent risk duction. We document how aging affects various parts of factor for many of the most common diseases afflicting the the immune system, B cells, T cells, and so forth, in an effort aging population of the world. -
CD6 Is a Target for Cancer Immunotherapy
CD6 is a target for cancer immunotherapy Jeffrey H. Ruth, … , Feng Lin, David A Fox JCI Insight. 2021. https://doi.org/10.1172/jci.insight.145662. Research In-Press Preview Immunology Graphical abstract Find the latest version: https://jci.me/145662/pdf CD6 is a Target for Cancer Immunotherapy Jeffrey H. Ruth1*, Mikel Gurrea-Rubio1*, Kalana S. Athukorala1, Stephanie M. Rasmussen1, Daniel P. Weber1, Peggy Randon1, Rosemary J. Gedert1, Matthew E. Lind 1, M. Asif Amin1, Phillip L. Campbell1, Pei-Suen Tsou1, Yang Mao-Draayer2, Qi Wu2, Thomas M. Lanigan1, Venkateshwar G. Keshamouni3, Nora G. Singer4,5, Feng Lin6, David A. Fox1 1Division of Rheumatology, 2Department of Neurology and 3Division of Pulmonary & Critical Medicine, University of Michigan, Ann Arbor, MI. 4Case Western Reserve University, 5Division of Rheumatology, MetroHealth Medical Center, Cleveland, OH; 6Department of Immunity and Inflammation, Lerner Research institute, Cleveland Clinic, Cleveland, OH *these authors contributed equally to this study Correspondence to: Jeffrey H. Ruth, PhD University of Michigan Medical School Department of Medicine, Division of Rheumatology Email: [email protected] and David A. Fox, MD University of Michigan Medical School Department of Medicine, Division of Rheumatology Email: [email protected] Conflicts of interest: none Keywords: CD6, CD318, immune checkpoint, cancer Running title: Inhibition of lymphocyte CD6 reduces cancer progression Abstract Limitations of checkpoint inhibitor cancer immunotherapy include induction of autoimmune syndromes and resistance of many cancers. Since CD318, a novel CD6 ligand, is associated with aggressiveness and metastatic potential of human cancers, we tested the effect of an anti-CD6 monoclonal antibody, UMCD6, on killing of cancer cells by human lymphocytes.